Paper Info
Title
A New Approach to White Blood Cell Nucleus Segmentation Based on Gram-Schmidt Orthogonalization
Abstract
The differential counting of white blood cells provides invaluable information to hematologist for diagnosis and treatment of many diseases. Manually counting of white blood cells is a tiresome, time-consuming and susceptible to error procedure. Due to the tedious nature of this process, an automatic system is preferable. In this automatic process, Segmentation of white blood cells is one of the most important stages. The nucleus of white blood cells has the most information about the type of white blood cells, thus an exact segmentation seems to be helpful for other stages of automatic recognition of white blood cells. In this paper, we introduced a novel method based on orthogonality theory and Gram-Schmidt process for segmenting the nuclei of white blood cells. For evaluation of results, we compared our proposed method with a hematologist manual segmentation. Results show robustness of this technique for segmentation of nuclei, while this method is very simple to implement.
Year
DOI
Venue
2009
10.1109/ICDIP.2009.19
ICDIP
Keywords
Field
DocType
hematologist manual segmentation,invaluable information,automatic recognition,gram-schmidt process,exact segmentation,automatic process,white blood cell,novel method,automatic system,white blood cell nucleus,new approach,gram-schmidt orthogonalization,cancer,image recognition,data mining,biomedical imaging,gram schmidt process,intelligent control,orthogonality,image segmentation,gram schmidt orthogonalization,process control,microscopy,feature extraction
Computer vision,Nucleus,Hematologist,Gram–Schmidt process,Segmentation,Computer science,Robustness (computer science),Image segmentation,Feature extraction,Artificial intelligence,White blood cell
Conference
Citations 
PageRank 
References 
8
0.73
12
Authors
4
Name
Order
Citations
PageRank
S. H. Rezatofighi1101.12
Hamid Soltanian-Zadeh224422.92
R. Sharifian380.73
R. A. Zoroofi4666.01